New York, NY – BlackRock’s Julia-powered Aladdin analytics and risk management platform was featured in yesterday’s New York Times in an article titled “At BlackRock, Machines Are Rising Over Managers To Pick Stocks”.

BlackRock is the world’s largest asset manager, with $5.1 trillion under management. BlackRock’s trademark Aladdin platform was built using Julia, the fastest modern high performance open source computing language for data and analytics.

About Julia Computing and Julia

Julia Computing (JuliaComputing.com) was founded in 2015 by the co-creators of the Julia language to provide support to businesses and researchers who use Julia.

Julia is the fastest modern high performance open source computing language for data and analytics. It combines the functionality and ease of use of Python, R, Matlab, SAS and Stata with the speed of Java and C++. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity. With more than 1 million downloads and +161% annual growth, Julia adoption is growing rapidly in finance, energy, robotics, genomics and many other fields.

1. Julia is lightning fast. Julia provides speed improvements up to
   1,000x for insurance model estimation, 225x for parallel
   supercomputing image analysis and 11x for macroeconomic modeling.

2. Julia is easy to learn. Julia’s flexible syntax is familiar and
   comfortable for users of Python, R and Matlab.

3. Julia integrates well with existing code and platforms. Users of
   Python, R, Matlab and other languages can easily integrate their
   existing code into Julia.

4. Elegant code. Julia was built from the ground up for
   mathematical, scientific and statistical computing, and has advanced
   libraries that make coding simple and fast, and dramatically reduce
   the number of lines of code required – in some cases, by 90%
   or more.

5. Julia solves the two language problem. Because Julia combines
   the ease of use and familiar syntax of Python, R and Matlab with the
   speed of C, C++ or Java, programmers no longer need to estimate
   models in one language and reproduce them in a faster
   production language. This saves time and reduces error and cost.

Julia users, partners and employers looking to hire Julia programmers in 2017 include: Google, Apple, Amazon, Facebook, IBM, Intel, Microsoft, BlackRock, Capital One, PricewaterhouseCoopers, Ford, Oracle, Comcast, DARPA, Moore Foundation, Federal Reserve Bank of New York (FRBNY), UC Berkeley Autonomous Race Car (BARC), Federal Aviation Administration (FAA), MIT Lincoln Labs, Nobel Laureate Thomas J. Sargent, Brazilian National Development Bank (BNDES), Conning, Berkery Noyes, BestX, Path BioAnalytics, Invenia, AOT Energy, AlgoCircle, Trinity Health, Gambit, Augmedics, Tangent Works, Voxel8, Massachusetts General Hospital, NaviHealth, Farmers Insurance, Pilot Flying J, Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC), Oak Ridge National Laboratory, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, National Renewable Energy Laboratory, MIT, Caltech, Stanford, UC Berkeley, Harvard, Columbia, NYU, Oxford, NUS, UCL, Nantes, Alan Turing Institute, University of Chicago, Cornell, Max Planck Institute, Australian National University, University of Warwick, University of Colorado, Queen Mary University of London, London Institute of Cancer Research, UC Irvine, University of Kaiserslautern.

Julia is being used to: analyze images of the universe and research dark matter, drive parallel supercomputing, diagnose medical conditions, provide surgeons with real-time imagery using augmented reality, analyze cancer genomes, manage 3D printers, pilot self-driving racecars, build drones, improve air safety, manage the electric grid, provide analytics for foreign exchange trading, energy trading, insurance, regulatory compliance, macroeconomic modeling, sports analytics, manufacturing and much, much more.

Julia Computing invites to the Julia in Finance Seminar in London on the 16th of March, organised in association with the CQF Institute. This event will introduce you to Julia, the easy-to-learn high-performance mathematical programming language that is taking the finance industry by storm.

The Julia in Finance Seminar takes place on Thursday, March 16th from 6:00 PM to 9 PM followed by refreshments and networking. The venue for this event is the Fitch Learning, The Corn Exchange, 55 Mark Lane, London, EC3R 7NE.

Come find out how quants, traders and data scientists from hedge funds, investment banks, and across financial services industry worldwide are using Julia to gain a mathematical computing advantage over their competitors by processing more data up to 1,000x faster than before. See how Julia enables innovation in the fintech and regtech sectors, helping companies and regulators keep ahead of a fast changing market.

There will be product demos, benchmarks, customer stories and use cases in Finance and Insurance, especially around trading, risk analytics and asset management among others.

Agenda

The event is free to attend in person, and will also be live-streamed worldwide. Please register below to reserve your seat.

About Julia

Julia is the simplest, fastest and most powerful numerical computing language available today. Julia combines the functionality of quantitative environments such as Python and R, with the speed of production programming languages like Java and C++ to solve big data and analytics problems. Julia delivers dramatic improvements in simplicity, speed, capacity, and productivity for data scientists, algorithmic traders, quants, scientists, and engineers who need to solve massive computational problems quickly and accurately.

Julia offers an unbeatable combination of simplicity and productivity with speed that is thousands of times faster than other mathematical, scientific and statistical computing languages.

Partners and users include: Intel, The Federal Reserve Bank of New York, Lincoln Laboratory (MIT), The Moore Foundation and a number of private sector finance and industry leaders, including several of the world’s leading hedge funds, investment banks, asset managers and insurers.

About Julia Computing, Inc.

Julia Computing, Inc. was founded in 2015 to develop products around Julia such as JuliaFin. These products help financial firms leverage the 1,000x improvement in speed and productivity that Julia provides for trading, risk analytics, asset management, macroeconomic modeling and other areas. Products of Julia Computing make Julia easy to develop, easy to deploy and easy to scale.

About CQF Institute

Part of Fitch Learning, the CQF Institute is the awarding body for the Certificate in Quantitative Finance and provides a platform for educating and building the quantitative finance community around the globe. Promoting the highest standard in practical financial engineering, the Institute offers its members exclusive access to educational content featured on the Institute website, keeping its members up to date on the latest quant finance industry practices.

Copenhagen, Denmark – Danske Bank, Denmark’s largest bank, announced that JuliaPro will be available on Microsoft Azure’s Data Science Virtual Machine (DSVM) for participants in the Business Analytics Challenge 2017.

The Business Analytics Challenge 2017 is sponsored by Danske Bank, Microsoft and KMD. The competition is open to all undergraduate and master’s degree students in Denmark and the first prize is 75 thousand kroner. Registration is open until March 31.

This announcement comes two months after the release of JuliaPro and one month after JuliaPro launched on Microsoft Azure’s Data Science Virtual Machine (DSVM).

Viral Shah, Julia Computing CEO says, “We are thrilled that Julia adoption is accelerating so rapidly during the first quarter of 2017. In the last three months, we introduced the new JuliaPro and launched it on the world’s two largest cloud environments: Amazon’s AWS and Microsoft Azure’s Data Science Virtual Machine (DSVM). Julia Computing wishes the best of luck to all contestants in the Danske Bank Business Analytics Challenge 2017.”

About Julia Computing and Julia

Julia Computing (JuliaComputing.com) was
founded in 2015 by the co-creators of the Julia language to provide
support to businesses and researchers who use Julia.

Julia is the fastest modern high performance open source computing language for data and analytics. It combines the functionality and ease of use of Python, R, Matlab, SAS and Stata with the speed of Java and C++. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity.

1. Julia is lightning fast. Julia provides speed improvements up to
   1,000x for insurance model estimation, 225x for parallel
   supercomputing image analysis and 11x for macroeconomic modeling.

2. Julia is easy to learn. Julia’s flexible syntax is familiar and
   comfortable for users of Python, R and Matlab.

3. Julia integrates well with existing code and platforms. Users of
   Python, R, Matlab and other languages can easily integrate their
   existing code into Julia.

4. Elegant code. Julia was built from the ground up for
   mathematical, scientific and statistical computing, and has advanced
   libraries that make coding simple and fast, and dramatically reduce
   the number of lines of code required – in some cases, by 90%
   or more.

5. Julia solves the two language problem. Because Julia combines
   the ease of use and familiar syntax of Python, R and Matlab with the
   speed of C, C++ or Java, programmers no longer need to estimate
   models in one language and reproduce them in a faster
   production language. This saves time and reduces error and cost.

Employers looking to hire Julia programmers in 2017 include: Google, Apple, Amazon, Facebook, IBM, BlackRock, Capital One, PricewaterhouseCoopers, Ford, Oracle, Comcast, Massachusetts General Hospital, NaviHealth, Harvard University, Columbia University, Farmers Insurance, Pilot Flying J, Los Alamos National Laboratory, Oak Ridge National Laboratory and the National Renewable Energy Laboratory.

Julia users and partners include: Amazon, IBM, Intel, Microsoft, DARPA, Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC), Federal Aviation Administration (FAA), MIT Lincoln Labs, Moore Foundation, Nobel Laureate Thomas J. Sargent, Federal Reserve Bank of New York (FRBNY), Capital One, Brazilian National Development Bank (BNDES), BlackRock, Conning, Berkery Noyes, BestX, Path BioAnalytics, Invenia, AOT Energy, AlgoCircle, Trinity Health, Gambit, Augmedics, Tangent Works, Voxel8, UC Berkeley Autonomous Race Car (BARC) and many of the world’s largest investment banks, asset managers, fund managers, foreign exchange analysts, insurers, hedge funds and regulators.

Universities and institutes using Julia include: MIT, Caltech, Stanford, UC Berkeley, Harvard, Columbia, NYU, Oxford, NUS, UCL, Nantes, Alan Turing Institute, University of Chicago, Cornell, Max Planck Institute, Australian National University, University of Warwick, University of Colorado, Queen Mary University of London, London Institute of Cancer Research, UC Irvine, University of Kaiserslautern.

Julia is being used to: analyze images of the universe and research dark matter, drive parallel computing on supercomputers, diagnose medical conditions, provide surgeons with real-time imagery using augmented reality, analyze cancer genomes, manage 3D printers, pilot self-driving racecars, build drones, improve air safety, manage the electric grid, provide analytics for foreign exchange trading, energy trading, insurance, regulatory compliance, macroeconomic modeling, sports analytics, manufacturing and much, much more.